Background—: Cardiovascular disease burden and treatment patterns among patients with familial hypercholesterolemia (FH) in the United States remain poorly described. In 2013, the FH Foundation launched the Cascade Screening for Awareness and Detection (CASCADE) of FH Registry to address this knowledge gap. Methods and Results—: We conducted a cross-sectional analysis of 1295 adults with heterozygous FH enrolled in the CASCADE-FH Registry from 11 US lipid clinics. Median age at initiation of lipid-lowering therapy was 39 years, and median age at FH diagnosis was 47 years. Prevalent coronary heart disease was reported in 36% of patients, and 61% exhibited 1 or more modifiable risk factors. Median untreated low-density lipoprotein cholesterol (LDL-C) was 239 mg/dL. At enrollment, median LDL-C was 141 mg/dL; 42% of patients were taking high-intensity statin therapy and 45% received >1 LDL-lowering medication. Among FH patients receiving LDL-lowering medication(s), 25% achieved an LDL-C 1 LDL-lowering medication (1.80; 1.34–2.41). Conclusions—: FH patients in the CASCADE-FH Registry are diagnosed late in life and often do not achieve adequate LDL-C lowering, despite a high prevalence of coronary heart disease and risk factors. These findings highlight the need for earlier diagnosis of FH and initiation of lipid-lowering therapy, more consistent use of guideline-recommended LDL-lowering therapy, and comprehensive management of traditional coronary heart disease risk factors.

This JAMA Insights article explains process of cascade screening for familial hypercholesterolemia and its efficacy in reducing risk of atherosclerotic cardiova

Background: Accurate, high-throughput genotyping allows the fine characterization of genetic ancestry. Here we applied recently developed statistical and computational techniques to the question of African ancestry in African Americans by using data on more than 450,000 single-nucleotide polymorphisms (SNPs) genotyped in 94 Africans of diverse geographic origins included in the HGDP, as well as 136 African Americans and 38 European Americans participating in the Atherosclerotic Disease Vascular Function and Genetic Epidemiology (ADVANCE) study. To focus on African ancestry, we reduced the data to include only those genotypes in each African American determined statistically to be African in origin. Results: From cluster analysis, we found that all the African Americans are admixed in their African components of ancestry, with the majority contributions being from West and West-Central Africa, and only modest variation in these African-ancestry proportions among individuals. Furthermore, by principal components analysis, we found little evidence of genetic structure within the African component of ancestry in African Americans. Conclusions: These results are consistent with historic mating patterns among African Americans that are largely uncorrelated to African ancestral origins, and they cast doubt on the general utility of mtDNA or Y-chromosome markers alone to delineate the full African ancestry of African Americans. Our results also indicate that the genetic architecture of African Americans is distinct from that of Africans, and that the greatest source of potential genetic stratification bias in case-control studies of African Americans derives from the proportion of European ancestry.

Accurate and consistent variant classification is imperative for incorporation of rapidly developing sequencing technologies into genomic medicine for improved patient care. An essential requirement for achieving standardized and reliable variant interpretation is data sharing, facilitated by a centralized open‐source database. Familial hypercholesterolemia (FH) is an exemplar of the utility of such a resource: it has a high incidence, a favorable prognosis with early intervention and treatment, and cascade screening can be offered to families if a causative variant is identified. ClinVar, an NCBI‐funded resource, has become the primary repository for clinically relevant variants in Mendelian disease, including FH. Here, we present the concerted efforts made by the Clinical Genome Resource, through the FH Variant Curation Expert Panel and global FH community, to increase submission of FH‐associated variants into ClinVar. Variant‐level data was categorized by submitter, variant characteristics, classification method, and available supporting data. To further reform interpretation of FH‐associated variants, areas for improvement in variant submissions were identified; these include a need for more detailed submissions and submission of supporting variant‐level data, both retrospectively and prospectively. Collaborating to provide thorough, reliable evidence‐based variant interpretation will ultimately improve the care of FH patients.

Objective: Statin treatment reduces the risk of atherosclerotic cardiovascular disease but is associated with a modest increased risk of type 2 diabetes, especially in those with insulin resistance or prediabetes. Our objective was to determine the physiological mechanism for the increased type 2 diabetes risk. Approach and Results: We conducted an open-label clinical trial of atorvastatin 40 mg daily in adults without known atherosclerotic cardiovascular disease or type 2 diabetes at baseline. The co-primary outcomes were changes at 10 weeks versus baseline in insulin resistance as assessed by steady-state plasma glucose during the insulin suppression test and insulin secretion as assessed by insulin secretion rate area under the curve (ISR _AUC ) during the graded-glucose infusion test. Secondary outcomes included glucose and insulin, both fasting and during oral glucose tolerance test. Of 75 participants who enrolled, 71 completed the study (median age 61 years, 37% women, 65% non-Hispanic White, median body mass index, 27.8 kg/m ² ). Atorvastatin reduced LDL (low-density lipoprotein)-cholesterol (median decrease 53%, P <0.001) but did not change body weight. Compared with baseline, atorvastatin increased insulin resistance (steady-state plasma glucose) by a median of 8% ( P =0.01) and insulin secretion (ISR _AUC ) by a median of 9% ( P <0.001). There were small increases in oral glucose tolerance test glucose _AUC (median increase, 0.05%; P =0.03) and fasting insulin (median increase, 7%; P =0.01). Conclusions: In individuals without type 2 diabetes, high-intensity atorvastatin for 10 weeks increases insulin resistance and insulin secretion. Over time, the risk of new-onset diabetes with statin use may increase in individuals who become more insulin resistant but are unable to maintain compensatory increases in insulin secretion. Registration: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT02437084. Graphic A graphic abstract is available for this article.

Familial hypercholesterolemia (FH) is an underdiagnosed dominant genetic condition affecting approximately 0.4% of the population and has up to a 20-fold increased risk of coronary artery disease if untreated. Simple screening strategies have false positive rates greater than 95%. As part of the FH Foundation′s FIND FH initiative, we developed a classifier to identify potential FH patients using electronic health record (EHR) data at Stanford Health Care. We trained a random forest classifier using data from known patients (n = 197) and matched non-cases (n = 6590). Our classifier obtained a positive predictive value (PPV) of 0.88 and sensitivity of 0.75 on a held-out test-set. We evaluated the accuracy of the classifier′s predictions by chart review of 100 patients at risk of FH not included in the original dataset. The classifier correctly flagged 84% of patients at the highest probability threshold, with decreasing performance as the threshold lowers. In external validation on 466 FH patients (236 with genetically proven FH) and 5000 matched non-cases from the Geisinger Healthcare System our FH classifier achieved a PPV of 0.85. Our EHR-derived FH classifier is effective in finding candidate patients for further FH screening. Such machine learning guided strategies can lead to effective identification of the highest risk patients for enhanced management strategies.